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Publikationen - Molekulare Signalverarbeitung

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Bücher und Buchkapitel

Klemm, S.; Buhl, J.; Möller, B.; Bürstenbinder, K.; Quantitative analysis of microtubule organization in leaf epidermis pavement cells (Hussey, P.J., Wang, P.). The Plant Cytoskeleton 2604, 43-61, (2023) ISBN: 978-1-0716-2866-9 DOI: 10.1007/978-1-0716-2867-6_4

Leaf epidermis pavement cells form highly complex shapes with interlocking lobes and necks at their anticlinal walls. The microtubule cytoskeleton plays essential roles in pavement cell morphogenesis, in particular at necks. Vice versa, shape generates stress patterns that regulate microtubule organization. Genetic or pharmacological perturbations that affect pavement cell shape often affect microtubule organization. Pavement cell shape and microtubule organization are therefore closely interconnected. Here, we present commonly used approaches for the quantitative analysis of pavement cell shape characteristics and of microtubule organization. In combination with ablation experiments, these methods can be applied to investigate how different genotypes (or treatments) affect the organization and stress responsiveness of the microtubule cytoskeleton.
Bücher und Buchkapitel

Poeschl, Y.; Möller, B.; Müller, L.; Bürstenbinder, K.; User-friendly assessment of pavement cell shape features with PaCeQuant: Novel functions and tools (Charles T. Anderson, Elizabeth S. Haswell, Ram Dixit). Methods Cell Biol. 160, 349-363, (2020) DOI: 10.1016/bs.mcb.2020.04.010

Leaf epidermis pavement cells develop complex jigsaw puzzle-like shapes in many plant species, including the model plant Arabidopsis thaliana. Due to their complex morphology, pavement cells have become a popular model system to study shape formation and coordination of growth in the context of mechanically coupled cells at the tissue level. To facilitate robust assessment and analysis of pavement cell shape characteristics in a high-throughput fashion, we have developed PaCeQuant and a collection of supplemental tools. The ImageJ-based MiToBo plugin PaCeQuant supports fully automatic segmentation of cell contours from microscopy images and the extraction of 28 shape features for each detected cell. These features now also include the Largest Empty Circle criterion as a proxy for mechanical stress. In addition, PaCeQuant provides a set of eight features for individual lobes, including the categorization as type I and type II lobes at two- and three-cell junctions, respectively. The segmentation and feature extraction results of PaCeQuant depend on the quality of input images. To allow for corrections in case of local segmentation errors, the LabelImageEditor is provided for user-friendly manual postprocessing of segmentation results. For statistical analysis and visualization, PaCeQuant is supplemented with the R package PaCeQuantAna, which provides statistical analysis functions and supports the generation of publication-ready plots in ready-to-use R workflows. In addition, we recently released the FeatureColorMapper tool which overlays feature values over cell regions for user-friendly visual exploration of selected features in a set of analyzed cells.
Bücher und Buchkapitel

Möller, B.; Bürstenbinder, K.; Semi-Automatic Cell Segmentation from Noisy Image Data for Quantification of Microtubule Organization on Single Cell Level 199-203, (2019) ISBN: 978-1-5386-3641-1 DOI: 10.1109/ISBI.2019.8759145

The structure of the microtubule cytoskeleton provides valuable information related to morphogenesis of cells. The cytoskeleton organizes into diverse patterns that vary in cells of different types and tissues, but also within a single tissue. To assess differences in cytoskeleton organization methods are needed that quantify cytoskeleton patterns within a complete cell and which are suitable for large data sets. A major bottleneck in most approaches, however, is a lack of techniques for automatic extraction of cell contours. Here, we present a semi-automatic pipeline for cell segmentation and quantification of microtubule organization. Automatic methods are applied to extract major parts of the contours and a handy image editor is provided to manually add missing information efficiently. Experimental results prove that our approach yields high-quality contour data with minimal user intervention and serves a suitable basis for subsequent quantitative studies.
Bücher und Buchkapitel

Möller, B.; Zergiebel, L.; Bürstenbinder, K.; Quantitative and Comparative Analysis of Global Patterns of (Microtubule) Cytoskeleton Organization with CytoskeletonAnalyzer2D (Cvrčková, F. & Žárský, V., eds.). Methods Mol. Biol. 1992, 151-171, (2019) ISBN: 978-1-4939-9469-4 DOI: 10.1007/978-1-4939-9469-4_10

The microtubule cytoskeleton plays important roles in cell morphogenesis. To investigate the mechanisms of cytoskeletal organization, for example, during growth or development, in genetic studies, or in response to environmental stimuli, image analysis tools for quantitative assessment are needed. Here, we present a method for texture measure-based quantification and comparative analysis of global microtubule cytoskeleton patterns and subsequent visualization of output data. In contrast to other approaches that focus on the extraction of individual cytoskeletal fibers and analysis of their orientation relative to the growth axis, CytoskeletonAnalyzer2D quantifies cytoskeletal organization based on the analysis of local binary patterns. CytoskeletonAnalyzer2D thus is particularly well suited to study cytoskeletal organization in cells where individual fibers are difficult to extract or which lack a clearly defined growth axis, such as leaf epidermal pavement cells. The tool is available as ImageJ plugin and can be combined with publicly available software and tools, such as R and Cytoscape, to visualize similarity networks of cytoskeletal patterns.
Bücher und Buchkapitel

Möller, B.; Poeschl, Y.; Klemm, S.; Bürstenbinder, K.; Morphological Analysis of Leaf Epidermis Pavement Cells with PaCeQuant (Cvrčková, F. & Žárský, V., eds.). Methods Mol. Biol. 1992, 329-349, (2019) ISBN: 978-1-4939-9469-4 DOI: 10.1007/978-1-4939-9469-4_22

Morphological analysis of cell shapes requires segmentation of cell contours from input images and subsequent extraction of meaningful shape descriptors that provide the basis for qualitative and quantitative assessment of shape characteristics. Here, we describe the publicly available ImageJ plugin PaCeQuant and its associated R package PaCeQuantAna, which provides a pipeline for fully automatic segmentation, feature extraction, statistical analysis, and graphical visualization of cell shape properties. PaCeQuant is specifically well suited for analysis of jigsaw puzzle-like leaf epidermis pavement cells from 2D input images and supports the quantification of global, contour-based, skeleton-based, and pavement cell-specific shape descriptors.
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